plot_MADE: Generic plot function for 'MADE' objects

Description

Create a faceted plot displaying the results of a set of power analyses. This is a generic function to make facet_grid plots, with specific methods defined for power_MADE, mdes_MADE, and min_studies_MADE objects.

Usage

plot_MADE(
  data,
  v_lines,
  legend_position,
  color,
  numbers,
  number_size,
  numbers_ynudge,
  caption,
  x_lab,
  x_breaks,
  x_limits,
  y_breaks,
  y_limits,
  y_expand = NULL,
  warning,
  traffic_light_assumptions,
  ...
)

Value

A ggplot object

Arguments

data: Data/object for which the plot should be made.
v_lines: Integer or vector to specify vertical line(s) in within each plot. Default is NULL.
legend_position: Character string to specify position of legend. Default is "bottom".
color: Logical indicating whether to use color in the plot(s). Default is TRUE.
numbers: Logical indicating whether to number the plots. Default is TRUE.
number_size: Integer value specifying the size of the (optional) plot numbers. Default is 2.5.
numbers_ynudge: Integer value for vertical nudge of the (optional) plot numbers.
caption: Logical indicating whether to include a caption with detailed information regarding the analysis. Default is TRUE.
x_lab: Title for the x-axis. If NULL (the default), the x_lab is specified automatically.
x_breaks: Optional vector to specify breaks on the x-axis. Default is NULL.
x_limits: Optional vector of length 2 to specify the limits of the x-axis. Default is NULL, which allows limits to be determined automatically from the data.
y_breaks: Optional vector to specify breaks on the y-axis.
y_limits: Optional vector of length 2 to specify the limits of the y-axis.
y_expand: Optional vector to expand the limits of the y-axis. Default is NULL.
warning: Logical indicating whether warnings should be returned when multiple models appear in the data. Default is TRUE.
traffic_light_assumptions: Optional logical to specify coloring of strips of the facet grids to emphasize assumptions about the likelihood the given analytical scenario. See Vembye, Pustejovsky, & Pigott (In preparation) for further details.
...: Additional arguments available for some classes of objects.

References

Vembye, M. H., Pustejovsky, J. E., & Pigott, T. D. (In preparation). Conducting power analysis for meta-analysis of dependent effect sizes: Common guidelines and an introduction to the POMADE R package.

Examples

Run this code

power_dat <-
  power_MADE(
    J = c(50, 56),
    mu = 0.15,
    tau = 0.1,
    omega = 0.05,
    rho = 0,
    sigma2_dist = 4 / 200,
    n_ES_dist = 6
  )

power_example <-
  plot_MADE(
   data = power_dat,
   power_min = 0.8,
   expected_studies = c(52, 54),
   warning = FALSE,
   caption = TRUE,
   color = TRUE,
   model_comparison = FALSE,
   numbers = FALSE
   )

power_example